THAI FOREST ECOLOGICAL RESEARCH JOURNAL

ISSN 2586-9566 (Print) ISSN 2985-0789 (Online)

Applying Geographic Information System to Evaluate Risk Areas of Illegal Logging in Conservation Areas at Maehongson Province

Chitiphan Phayayam1, Kamonporn Panngom2, Itsaree Howpinjai3 and Torlarp Kamyo4*
1Department Forest Management, Maejo University Phrae Campus, Rong Kwang, Phare 54140
2Department of Applied Biology, Maejo University Phrae Campus, Rong Kwang, Phare 54140
3Department of Forest Industry Technology, Maejo University Phrae Campus, Rong Kwang, Phare 54140
4Department of Agroforestry, Maejo University Phrae Campus, Rong Kwang, Phare 54140
*Corresponding author: Email: torlarp66@gmail.com
Abstract

Background and Objectives: Illegal logging in protected forest areas is a significant problem that has a major impact on biodiversity and the habitats of forest animals. The objective of this study was to analyze the factors influencing illegal logging and assess the areas at risk of illegal logging in Mae Hong Son province, Thailand.

Methodology:  The study used data on observed logging points in the period between 2020-2021, and employed statistical modeling with eight environmental factors: elevation above sea level, slope, aspect, distance from rivers, distance from roads, distance from villages, distance from patrol station units, and NDVI. The MaxEnt program and geographic information system (GIS) were applied. 

Main Results: The study found that the factors with the highest impact on illegal logging were elevation above sea level, distance from roads, and slope. The statistically significant AUC was 0.805. The results indicated that the area at low risk of illegal logging covered approximately 2,457,988.34 rai, accounting for 78.58% of the total area. The moderately high-risk area covered 590,761.76 rai, accounting for 18.89%, and the high-risk area covered 79,127.48 rai, accounting for 2.53%. 

Conclusion: The area with a high risk of illegal logging is an area near the road, with low slopes, and at an elevation of 100 to 400 meters above mean sea level. These findings can be used as a tool for planning and implementing measures to prevent and combat illegal logging in conservation areas. They can be applied to plan forest patrolling operations based on the level of risk in each area, thus improving the effectiveness of conservation efforts in the conservation areas.

Keywords: Risk assessment; GIS; Maximum Entropy model; Conservation area


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